Join Michele Vallisneri for an in-depth discussion in this video What you need to know, part of Python: Data Analysis.
- Before getting started with this course, you'll want to have a basic working knowledge of programming in Python. Although we will review the aspects of Python that are essential to any data analysis task, I will not teach you about every feature of Python that we will meet. It will also be helpful to have an understanding of basic mathematical and statistical concepts, such as logic operations, functions, averages, minima, and maxima. Nowadays, data are almost always collected electronically. This means that to manipulate them and analyze them, you need programming and even ethical hacking skills.
Effective data analysis requires also a knowledge of mathematics and statistics and a familiarity with the particular field that you're studying. Having a strong programming foundation and being able to rely on a robust tool such as Python will make it easier for you to learn mathematical skills, not just by study, but also by experimentation, and to get to know your field by way of exploration.
- Writing and running Python in iPython
- Using Python lists and dictionaries
- Creating NumPy arrays
- Indexing and slicing in NumPy
- Downloading and parsing data files into NumPy and Pandas
- Using multilevel series in Pandas
- Aggregating data in Pandas
Skill Level Intermediate
Q: The course shows how to download files from FTP and web servers using Python 3.X. How do I do the same thing with Python 2.7?
A: First import urllib, then use urllib.urlretrieve(URL,filename). For instance, to download the stations.txt files used in the chapter 5 video “Downloading and parsing data files,” you’d do urllib.urlretrieve(‘ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/daily/ghcnd-stations.txt','stations.txt').
1. Installation and Setup
2. Refresher: Data Containers in Python
3. Word Anagrams in Python
4. Introduction to NumPy
5. Weather Data with NumPy
6. Introduction to Pandas
7. Baby Names with Pandas
Next steps1m 36s
- Mark as unwatched
- Mark all as unwatched
Are you sure you want to mark all the videos in this course as unwatched?
This will not affect your course history, your reports, or your certificates of completion for this course.Cancel
Take notes with your new membership!
Type in the entry box, then click Enter to save your note.
1:30Press on any video thumbnail to jump immediately to the timecode shown.
Notes are saved with you account but can also be exported as plain text, MS Word, PDF, Google Doc, or Evernote.